(untitled) (Publicaciones en Ciencias y Tecnología, 2015)
The functions library, called Basic Linear Algebra Subprograms (BLAS-1), is considered the programming standard in scientific computing. In this work, we focus on the analysis of various code optimization techniques to increase the computational performance of BLAS-1. In particular, we address a combinational approach to explore possible methods of encoding using unroll technique with di erent levels of depth, vector data programming with MMX and SSE for Intel processors. Using the main functions of BLAS-1, it was determined numerically a computational increase, expressed in mega-ops, up to 52% compared to the optimized BLAS-1 ATLAS library